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Search results for 'Forward models' (try it on Scholar)

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  1. Axel Cleeremans, Applying Forward Models to Sequence Learning: A Connectionist Implementation.score: 120.0
    The ability to process events in their temporal and sequential context is a fundamental skill made mandatory by constant interaction with a dynamic environment. Sequence learning studies have demonstrated that subjects exhibit detailed — and often implicit — sensitivity to the sequential structure of streams of stimuli. Current connectionist models of performance in the so-called Serial Reaction Time Task (SRT), however, fail to capture the fact that sequence learning can be based not only on sensitivity to the sequential associations (...)
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  2. Jeffrey Bowers (2013). How Do Forward Models Work? And Why Would You Want Them? Behavioral and Brain Sciences 36 (4):349-350.score: 120.0
    The project of coordinating perception, comprehension, and motor control is an exciting one, but I found it hard to follow some of Pickering & Garrod's (P&G's) arguments as presented. Consequently, my comment is not so much a disagreement with P&G but a query about the logic of forward models: It is not clear how they are supposed to work, nor why they are needed in this (or many other) contexts, and toward that end I present an alternative idea.
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  3. Martin J. Pickering & Simon Garrod (2013). Forward Models and Their Implications for Production, Comprehension, and Dialogue. Behavioral and Brain Sciences 36 (4):377-392.score: 120.0
    Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.
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  4. David Poeppel Xing Tian (2010). Mental Imagery of Speech and Movement Implicates the Dynamics of Internal Forward Models. Frontiers in Psychology 1.score: 120.0
    The classical concept of efference copies in the context of internal forward models has stimulated productive research in cognitive science and neuroscience. There are compelling reasons to argue for such a mechanism, but finding direct evidence in the human brain remains difficult. Here we investigate the dynamics of internal forward models from an unconventional angle: mental imagery, assessed while recording high temporal resolution neuronal activity using magnetoencephalography (MEG). We compare two overt and covert tasks; our covert, (...)
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  5. Robert J. Hartsuiker (2013). Are Forward Models Enough to Explain Self-Monitoring? Insights From Patients and Eye Movements. Behavioral and Brain Sciences 36 (4):357-358.score: 120.0
    At the core of Pickering & Garrod's (P&G's) theory is a monitor that uses forward models. I argue that this account is challenged by neuropsychological findings and visual world eye-tracking data and that it has two conceptual problems. I propose that conflict monitoring avoids these issues and should be considered a promising alternative to perceptual loop and forward modeling theories.
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  6. Robert Briscoe (2011). The Elusive Experience of Agency. Topics in Cognitive Science 3 (2):262-267.score: 90.0
    I here present some doubts about whether Mandik’s (2010) proposed intermediacy and recurrence constraints are necessary and sufficient for agentive experience. I also argue that in order to vindicate the conclusion that agentive experience is an exclusively perceptual phenomenon (Prinz, 2007), it is not enough to show that the predictions produced by forward models of planned motor actions are conveyed by mock sensory signals. Rather, it must also be shown that the outputs of “comparator” mechanisms that compare these (...)
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  7. Martin J. Pickering & Andy Clark (forthcoming). Getting Ahead: Forward Models and Their Place in Cognitive Architecture. Trends in Cognitive Sciences.score: 90.0
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  8. Xing Tian & David Poeppel (2010). Mental Imagery of Speech and Movement Implicates the Dynamics of Internal Forward Models. Frontiers in Psychology 1:166.score: 90.0
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  9. Michael I. Jordan & David E. Rumelhart (1992). Forward Models: Supervised Learning with a Distal Teacher. Cognitive Science 16 (3):307-354.score: 90.0
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  10. D. M. Wolpert & J. R. Flanagan (2009). Forward Models. In Bayne Tim, Cleeremans Axel & Wilken Patrick (eds.), The Oxford Companion to Consciousness. Oxford University Press. 294--296.score: 90.0
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  11. André Lee, Shinichi Furuya, Matthias Karst & Eckart Altenmüller (2013). Alteration in Forward Model Prediction of Sensory Outcome of Motor Action in Focal Hand Dystonia. Frontiers in Human Neuroscience 7.score: 80.0
    Focal hand dystonia in musicians is a movement disorder affecting highly trained movements. Rather than being a pure motor disorder related to movement execution only, movement planning, error prediction and sensorimotor integration are also impaired. Internal models, of which two types, forward and inverse models have been described and most likely processed in the cerebellum, are known to be involved in these tasks. Recent results indicate that the cerebellum may be involved in the pathophysiology of focal dystonia. (...)
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  12. Gary S. Dell (2013). Cascading and Feedback in Interactive Models of Production: A Reflection of Forward Modeling? Behavioral and Brain Sciences 36 (4):351-352.score: 74.0
    Interactive theories of lexical retrieval in language production assume that activation cascades from earlier to later processing levels, and feeds back in the reverse direction. This commentary invites Pickering & Garrod (P&G) to consider whether cascading and feedback can be seen as a form of forwarding modeling within a hierarchical production system.
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  13. Sa'idu Sulaiman (1998). Islamization of Knowledge: Background, Models and the Way Forward. The International Institute of Islamic Thought.score: 72.0
    On the implementation aspect of the Islamization of knowledge programme, there were also suggestions that my paper should provide readers with Al-Faruqi's ...
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  14. Opher Donchin & Amir Raz (2004). Where in the Brain Does the Forward Model Lurk? Behavioral and Brain Sciences 27 (3):402-403.score: 72.0
    The general applicability of forward models in brain function has previously been recognized. Grush's contribution centers largely on broadening the extent and scope of forward models. However, in his effort to expand and generalize, important distinctions may have been overlooked. A better grounding in the underlying physiology would have helped to illuminate such valuable differences and similarities.
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  15. Stephen R. Carpenter & Lance H. Gunderson (2001). Coping with Collapse: Ecological and Social Dynamics in Ecosystem Management Like Flight Simulators That Train Would-Be Aviators, Simple Models Can Be Used to Evoke People's Adaptive, Forward-Thinking Behavior, Aimed in This Instance at Sustainability of Human–Natural Systems. Bioscience 51 (6):451-457.score: 72.0
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  16. Thomas G. Fikes & James T. Townsend (1995). Moving Models of Motion Forward: Explication and a New Concept. Behavioral and Brain Sciences 18 (4):751.score: 72.0
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  17. Keith Morrison (2010). A Review of “Indra's Net: Alchemy and Chaos Theory as Models for Transformation” Robertson, Robin (with a Forward by Allan Combs). Wheaton, IL: Quest Books, 2009 (Notes, Bibliography, Credit Illustrations and Index, 175 Pp., $16.95 USD, Paperback, ISBN: 978-0-8356-0862-6). [REVIEW] World Futures 66 (8):626-629.score: 72.0
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  18. Gary M. Oppenheim (2013). Inner Speech as a Forward Model? Behavioral and Brain Sciences 36 (4):369-370.score: 72.0
    Pickering & Garrod (P&G) consider the possibility that inner speech might be a product of forward production models. Here I consider the idea of inner speech as a forward model in light of empirical work from the past few decades, concluding that, while forward models could contribute to it, inner speech nonetheless requires activity from the implementers.
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  19. Frederic Peters (2010). Consciousness as Recursive, Spatiotemporal Self-Location. Psychological Research.score: 60.0
    At the phenomenal level, consciousness arises in a consistently coherent fashion as a singular, unified field of recursive self-awareness (subjectivity) with explicitly orientational characteristics—that of a subject located both spatially and temporally in an egocentrically-extended domain. Understanding these twin elements of consciousness begins with the recognition that ultimately (and most primitively), cognitive systems serve the biological self-regulatory regime in which they subsist. The psychological structures supporting self-located subjectivity involve an evolutionary elaboration of the two basic elements necessary for extending self-regulation (...)
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  20. Chiara Gambi & Martin J. Pickering (2013). Prediction and Imitation in Speech. Frontiers in Psychology 4.score: 60.0
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  21. Wolfgang Prinz Anne Springer, Jim Parkinson (2013). Action Simulation: Time Course and Representational Mechanisms. Frontiers in Psychology 4.score: 60.0
    The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others’ actions implies a 'mirroring' of their activities, based on one’s own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the (...)
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  22. Cyrill Guy Martin Ott & Lutz Jäncke (2013). Processing of Self-Initiated Speech-Sounds is Different in Musicians. Frontiers in Human Neuroscience 7.score: 58.0
    Musicians and musically untrained individuals have been shown to differ in a variety of functional brain processes such as auditory analysis and sensorimotor interaction. At the same time, internally operating forward models are assumed to enable the organism to discriminate the sensory outcomes of self-initiated actions from other sensory events by deriving predictions from efference copies of motor commands about forthcoming sensory consequences. As a consequence, sensory responses to stimuli that are triggered by a self-initiated motor act are (...)
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  23. Björn Kralemann & Claas Lattmann (2013). Models as Icons: Modeling Models in the Semiotic Framework of Peirce's Theory of Signs. Synthese 190 (16):3397-3420.score: 54.0
    In this paper, we try to shed light on the ontological puzzle pertaining to models and to contribute to a better understanding of what models are. Our suggestion is that models should be regarded as a specific kind of signs according to the sign theory put forward by Charles S. Peirce, and, more precisely, as icons, i.e. as signs which are characterized by a similarity relation between sign (model) and object (original). We argue for this (1) (...)
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  24. Myrto I. Mylopoulos & David Pereplyotchik (2013). Is There Any Evidence for Forward Modeling in Language Production? Behavioral and Brain Sciences 36 (4):368-369.score: 48.0
    The neurocognitive evidence that Pickering & Garrod (P&G) cite in favor of positing forward models in speech production is not compelling. The data to which they appeal either cannot be explained by forward models, or can be explained by a more parsimonious model.
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  25. Steven French (2010). Keeping Quiet on the Ontology of Models. Synthese 172 (2):231 - 249.score: 46.0
    Stein once urged us not to confuse the means of representation with that which is being represented. Yet that is precisely what philosophers of science appear to have done at the meta-level when it comes to representing the practice of science. Proponents of the so-called ‘syntactic’ view identify theories as logically closed sets of sentences or propositions and models as idealised interpretations, or ‘theoruncula, as Braithwaite called them. Adherents of the ‘semantic’ approach, on the other hand, are typically characterised (...)
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  26. S. Kaplan, M. Weaver & Robert M. French (1990). Active Symbols and Internal Models: Towards a Cognitive Connectionism. [REVIEW] AI and Society 4 (1):51-71.score: 42.0
    In the first section of the article, we examine some recent criticisms of the connectionist enterprise: first, that connectionist models are fundamentally behaviorist in nature (and, therefore, non-cognitive), and second that connectionist models are fundamentally associationist in nature (and, therefore, cognitively weak). We argue that, for a limited class of connectionist models (feed-forward, pattern-associator models), the first criticism is unavoidable. With respect to the second criticism, we propose that connectionist modelsare fundamentally associationist but that this (...)
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  27. Marion Vorms & David Lagnado, The Role of Models in Mind and Science.score: 42.0
    During the last few decades, models have become the centre of attention in both cognitive science and philosophy of science. In cognitive science, the claim that humans reason with mental models, rather than mentally manipulate linguistic symbols, is the majority view. Similarly, philosophers of science almost unanimously acknowledge that models have to be taken as a central unit of analysis. Moreover, some philosophers of science and cognitive scientists have suggested that the cognitive hypothesis of mental models (...)
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  28. Nelly Grosset & Pierre Barrouillet (2003). On the Nature of Mental Models of Conditional: The Case of If , If Then , and Only If. Thinking and Reasoning 9 (4):289 – 306.score: 42.0
    It has recently been reported that forward inferences from if p then q sentences (i.e., from antecedent to consequent) were faster than backward inferences from consequent to antecedent (Barrouillet, Grosset, & Lecas, 2000). The standard mental model theory assumes that this directionality effect is a figural effect due to the order the information enters working memory, whereas we claim that it results from the nature of the mental models that represent oriented relations from hypothetical values introduced by the (...)
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  29. Brendan Clarke, Bert Leuridan & Jon Williamson (2013). Modelling Mechanisms with Causal Cycles. Synthese:1-31.score: 42.0
    Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for (...)
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  30. Stéphane Demri & Dov Gabbay (2000). On Modal Logics Characterized by Models with Relative Accessibility Relations: Part II. Studia Logica 66 (3):349-384.score: 42.0
    This work is divided in two papers (Part I and Part II). In Part I, we introduced the class of Rare-logics for which the set of terms indexing the modal operators are hierarchized in two levels: the set of Boolean terms and the set of terms built upon the set of Boolean terms. By investigating different algebraic properties satisfied by the models of the Rare-logics, reductions for decidability were established by faithfully translating the Rare-logics into more standard modal logics (...)
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  31. Margaret Exley (2007). Managing CEO Succession: New Models for a New Era. International Journal of Business Governance and Ethics 3 (2):139-149.score: 42.0
    External pressures have changed the context within which CEOs are succeeded. At the same time, chairmen are clear that this responsibility is personal to them and are increasingly changing the nature of the process. Two new models of CEO succession are identified: one where the Board actively partners with the incumbent CEO and the other a crisis model where the Chairman and the Board assure the active management of the succession process. In both cases, best practice is for the (...)
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  32. B. Vereijken & H. T. A. Whiting (1998). Hoist by Their Own Petard: The Constraints of Hierarchical Models. Behavioral and Brain Sciences 21 (5):705-705.score: 42.0
    In the context of the motor skill literature on observational learning and hierarchical skill structuring, Byrne & Russon's findings call into question their standpoint that great apes imitate the behaviour of role models at the programme level. The authors impose a hierarchical model on their observations without properly considering alternative explanations. One such possibility, which stems from a constraints perspective that they dismiss, is put forward.
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  33. M. Schilling & H. Cruse (2011). What's Next: Recruitment of a Grounded Predictive Body Model for Planning a Robot's Actions. Frontiers in Psychology 3:383-383.score: 40.0
    Even comparatively simple, reactive systems are able to control complex motor tasks, such as hexapod walking on unpredictable substrate. The capability of such a controller can be improved by introducing internal models of the body and of parts of the environment. Such internal models can be applied as inverse models, as forward models or to solve the problem of sensor fusion. Usually, separate models are used for these functions. Furthermore, separate models are used (...)
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  34. Jeff Prideaux (1996). Feed-Forward Activation in a Theoretical First-Order Biochemical Pathway Which Contains an Anticipatory Model. Acta Biotheoretica 44 (3-4).score: 40.0
    This paper explores the consequences of the theoretical forward activation enzymatic pathway A 0 A 1 A 2 A 3 where E 1 convents A 0 to A 1, E 2 converts A 1 to A 2 and E 3 converts A 2 to A 3. A 0, which is environmentally determined, also serves to activate (or modulate) the activity of E 3 in such a way as to keep the concentration of A 2 ([A 2]) constant at a (...)
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  35. Kelly C. Strong & Rhonda Wiley Jones (2005). A Model for Feed-Forward Assessment of Student Learning in Industry-Issues Courses. Proceedings of the International Association for Business and Society 16:379-380.score: 40.0
    The validity of assessment programs is increasingly important in higher education. Existing approaches to assessment are problematic because they eitherfail to provide timely feedback or have suspect measurement issues. We propose a feed-forward assessment model to help overcome these two limitations oftraditional assessment approaches.
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  36. Motoaki Sugiura (2013). Associative Account of Self-Cognition: Extended Forward Model and Multi-Layer Structure. Frontiers in Human Neuroscience 7.score: 40.0
    The neural correlates of “self” identified by neuroimaging studies differ depending on which aspects of self are addressed. Here, three categories of self are proposed based on neuroimaging findings and an evaluation of the likely underlying cognitive processes. The physical self, representing self-agency of action, body ownership, and bodily self-recognition, is supported by the sensory and motor association cortices located primarily in the right hemisphere. The interpersonal self, representing the attention or intentions of others directed at the self, is supported (...)
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  37. Jonathan Waskan (2011). A Vehicular Theory of Corporeal Qualia (a Gift to Computationalists). Philosophical Studies 152 (1):103 - 125.score: 36.0
    I have argued elsewhere that non-sentential representations that are the close kin of scale models can be, and often are, realized by computational processes. I will attempt here to weaken any resistance to this claim that happens to issue from those who favor an across-the-board computational theory of cognitive activity. I will argue that embracing the idea that certain computers harbor nonsentential models gives proponents of the computational theory of cognition the means to resolve the conspicuous disconnect between (...)
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  38. Laura Martignon & Michael Schmitt (1999). Simplicity and Robustness of Fast and Frugal Heuristics. Minds and Machines 9 (4):565-593.score: 36.0
    Intractability and optimality are two sides of one coin: Optimal models are often intractable, that is, they tend to be excessively complex, or NP-hard. We explain the meaning of NP-hardness in detail and discuss how modem computer science circumvents intractability by introducing heuristics and shortcuts to optimality, often replacing optimality by means of sufficient sub-optimality. Since the principles of decision theory dictate balancing the cost of computation against gain in accuracy, statistical inference is currently being reshaped by a vigorous (...)
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  39. Angelo Nm Recchia-Luciani (2012). Manipulating Representations. Biosemiotics 5 (1):95-120.score: 36.0
    The present paper proposes a definition for the complex polysemic concepts of consciousness and awareness (in humans as well as in other species), and puts forward the idea of a progressive ontological development of consciousness from a state of ‘childhood’ awareness, in order to explain that humans are not only able to manipulate objects, but also their mental representations. The paper builds on the idea of qualia intended as entities posing regular invariant requests to neural processes, trough the permanence (...)
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  40. Ivilin P. Stoianov Marco Zorzi, Alberto Testolin (2013). Modeling Language and Cognition with Deep Unsupervised Learning: A Tutorial Overview. Frontiers in Psychology 4.score: 36.0
    Deep unsupervised learning in stochastic recurrent neural networks with many layers of hidden units is a recent breakthrough in neural computation research. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. In this article we discuss the theoretical foundations of this approach and we review key issues related to training, testing and analysis of deep networks for modeling language and cognitive processing. The classic letter and word perception problem (...)
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  41. Alessandro Torza (2011). Models for Counterparts. Axiomathes 21 (4):553-579.score: 34.0
    Lewis proposed to test the validity of a modal thesis by checking whether its possible-world translation is a theorem of counterpart theory. However, that criterion fails to validate many standard modal laws, thus raising doubts about the logical adequacy of the Lewisian framework. The present paper considers systems of counterpart theory of increasing strength and shows how each can be motivated by exhibiting a suitable intended model. In particular, perfect counterpart theory validates all the desired modal laws and therefore provides (...)
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  42. Steven Lehar (2003). Gestalt Isomorphism and the Primacy of Subjective Conscious Experience: A Gestalt Bubble Model. Behavioral and Brain Sciences 26 (4):357-408.score: 32.0
    A serious crisis is identified in theories of neurocomputation, marked by a persistent disparity between the phenomenological or experiential account of visual perception and the neurophysiological level of description of the visual system. In particular, conventional concepts of neural processing offer no explanation for the holistic global aspects of perception identified by Gestalt theory. The problem is paradigmatic and can be traced to contemporary concepts of the functional role of the neural cell, known as the Neuron Doctrine. In the absence (...)
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  43. Rick Grush (2004). The Emulation Theory of Representation: Motor Control, Imagery, and Perception. Behavioral And Brain Sciences 27 (3):377-396.score: 30.0
    The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven (...)
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  44. Peter Langland-Hassan (2011). A Puzzle About Visualization. Phenomenology and the Cognitive Sciences 10 (2):145-173.score: 30.0
    Visual imagination (or visualization) is peculiar in being both free, in that what we imagine is up to us, and useful to a wide variety of practical reasoning tasks. How can we rely upon our visualizations in practical reasoning if what we imagine is subject to our whims? The key to answering this puzzle, I argue, is to provide an account of what constrains the sequence in which the representations featured in visualization unfold—an account that is consistent with its freedom. (...)
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  45. Pierre Jacob (2006). Why Visual Experience is Likely to Resist Being Enacted. Psyche 12 (1).score: 30.0
    Alva Noë’s version of the enactive conception in _Action in Perception_ is an important contribution to the study of visual perception. First, I argue, however, that it is unclear (at best) whether, as the enactivists claim, work on change blindness supports the denial of the existence of detailed visual representations. Second, I elaborate on what Noë calls the ‘puzzle of perceptual presence’. Thirdly, I question the enactivist account of perceptual constancy. Finally, I draw attention to the tensions between enactivism and (...)
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  46. Elliot C. Brown & Martin Brüne (2012). The Role of Prediction in Social Neuroscience. Frontiers in Human Neuroscience 6 (147):147-147.score: 30.0
    Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e. by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one’s own and (...)
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  47. Giovanni Pezzulo (2011). Grounding Procedural and Declarative Knowledge in Sensorimotor Anticipation. Mind and Language 26 (1):78-114.score: 30.0
    We propose a view of embodied representations that is alternative to both symbolic/linguistic approaches and purely sensorimotor views of cognition, and can account for procedural and declarative knowledge manipulation. In accordance with recent evidence in cognitive neuroscience and psychology, we argue that anticipatory and simulative mechanisms, which arose during evolution for action control and not for cognition, determined the first form of representational content and were exapted for increasingly sophisticated cognitive uses. In particular, procedural and declarative forms of knowledge can (...)
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  48. Rick Grush (2007). Skill Theory V2.0: Dispositions, Emulation, and Spatial Perception. Synthese 159 (3):389 - 416.score: 30.0
    An attempt is made to defend a general approach to the spatial content of perception, an approach according to which perception is imbued with spatial content in virtue of certain kinds of connections between perceiving organism's sensory input and its behavioral output. The most important aspect of the defense involves clearly distinguishing two kinds of perceptuo-behavioral skills—the formation of dispositions, and a capacity for emulation. The former, the formation of dispositions, is argued to by the central pivot of spatial content. (...)
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  49. Vittorio Gallese & Christian Keysers (2001). Mirror Neurons: A Sensorimotor Representation System. Behavioral and Brain Sciences 24 (5):983-984.score: 30.0
    Positing the importance of sensorimotor contingencies for perception is by no means denying the presence and importance of representations. Using the evidence of mirror neurons we will show the intrinsic relationship between action control and representation within the logic of forward models.
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  50. Peter Langland-Hassan (forthcoming). On Choosing What to Imagine. In P. Kung (ed.), Knowledge Through Imagination. Oxford University Press.score: 30.0
    If imagination is subject to the will, in the sense that people choose the content of their own imaginings, how is it that one nevertheless can learn from what one imagines? This chapter argues for a way forward in addressing this perennial puzzle, both with respect to propositional imagination and sensory imagination. Making progress requires looking carefully at the interplay between one’s intentions and various kinds of constraints that may be operative in the generation of imaginings. Lessons are drawn (...)
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